models:
- name: orders
table: public.orders
dimensions:
- name: status
type: categorical
- name: order_date
type: time
sql: created_at
metrics:
- name: revenue
agg: sum
sql: amount
- name: order_count
agg: countMODEL (
name orders,
table public.orders
);
DIMENSION (name status, type categorical);
DIMENSION (name order_date, type time, sql created_at);
METRIC (name revenue, agg sum, sql amount);
METRIC (name order_count, agg count);from sidemantic import Model, Dimension, Metric
orders = Model(
name="orders",
table="public.orders",
dimensions=[
Dimension(name="status", type="categorical"),
Dimension(name="order_date", type="time", sql="created_at"),
],
metrics=[
Metric(name="revenue", agg="sum", sql="amount"),
Metric(name="order_count", agg="count"),
],
)cubes:
- name: orders
sql_table: public.orders
dimensions:
- name: status
sql: status
type: string
- name: created_at
sql: created_at
type: time
measures:
- name: revenue
sql: amount
type: sum
- name: count
type: countsemantic_models:
- name: orders
model: ref('orders')
entities:
- name: order
type: primary
expr: order_id
dimensions:
- name: status
type: categorical
- name: order_date
type: time
type_params:
time_granularity: day
measures:
- name: revenue
agg: sum
expr: order_amount
- name: order_count
agg: countview: orders {
sql_table_name: public.orders ;;
dimension: status {
type: string
sql: ${TABLE}.status ;;
}
dimension_group: created {
type: time
timeframes: [date, week, month]
sql: ${TABLE}.created_at ;;
}
measure: revenue {
type: sum
sql: ${TABLE}.amount ;;
}
measure: count {
type: count
}
}source: orders is duckdb.table('orders') extend {
primary_key: order_id
dimension:
status is status
order_date is created_at
measure:
revenue is sum(amount)
order_count is count()
}id: orders
base_sql_table: public.orders
dimensions:
- id: status
type: string
- id: created_at
type: timestamp_tz
measures:
- id: revenue
func: sum
of: amount
- id: order_count
func: counttype: metrics_view
model: orders
timeseries: created_at
smallest_time_grain: day
dimensions:
- name: status
column: status
measures:
- name: total_revenue
expression: SUM(amount)
- name: total_orders
expression: COUNT(*)table_name: orders
main_dttm_col: created_at
schema: public
columns:
- column_name: status
type: VARCHAR
groupby: true
- column_name: created_at
is_dttm: true
metrics:
- metric_name: total_revenue
expression: SUM(amount)
- metric_name: order_count
expression: COUNT(*)name: orders
table_name: orders
schema: public
dimensions:
status:
type: string
sql: ${TABLE}.status
created_at:
type: timestamp
timeframes: [date, week, month]
measures:
total_revenue:
aggregate_type: sum
sql: ${orders.amount}
count:
aggregate_type: counttables:
- name: orders
base_table:
database: analytics
schema: public
table: orders
dimensions:
- name: status
expr: status
data_type: VARCHAR
time_dimensions:
- name: order_date
expr: created_at
data_type: TIMESTAMP
facts:
- name: revenue
expr: amount
default_aggregation: sum
- name: order_count
expr: 1
default_aggregation: sumsemantic_model:
- name: orders_analytics
datasets:
- name: orders
source: public.orders
fields:
- name: status
expression:
dialects:
- dialect: ANSI_SQL
expression: status
metrics:
- name: revenue
expression:
dialects:
- dialect: ANSI_SQL
expression: SUM(orders.amount)orders:
table: public.orders
dimensions:
status:
expr: _.status
created_at:
expr: _.created_at
is_time_dimension: true
measures:
revenue:
expr: _.amount.sum()
count:
expr: _.count()
